> ## Documentation Index > Fetch the complete documentation index at: https://tensorfuse.io/docs/llms.txt > Use this file to discover all available pages before exploring further. # Cheatsheet for Tensorkube users > Deploy serverless GPU applications on your AWS account Built with developer experience in mind, Tensorkube simplifies the process of deploying serverless GPU apps. Sometimes for advanced debugging use-cases you might want to know the underlying details of the deployment. This cheatsheet will equip you with the necessary commands to get the details of your deployment. ### Deploy command with all parameters `tensorkube deploy --gpus 1 --gpu-type a10g --cpu 2500 --memory 12000 --min-scale 1 --max-scale 10 --env staging --secret aws-secret --secret huggingface-secret` * `--cpu` is in millicores, 1000 = 1vCPU * `--memory` is in MB, 1024 = 1GB ### List all deployments Use `tensorkube list deployments --all` to get the details of your deployed apps including their names, status and their `HTTP endpoints`. Use `tensorkube list deployments --env ` for apps in an environment. ### Logs of a pod Use `tensorkube deployment logs --env ` to get the logs of a deployment/pod. This will show you the logs of the pod and help you debug any issues that might be present in the pod. ### SSH into a deployment / pod Use `tensorkube deployment ssh --env ` to ssh into a pod. This will help you debug any issues that might be present in the pod. ### Get details of a deployment `tensorkube deployment describe --env ` ### List all running pods Use `kubectl get pods -n ` to get the details of all the running pods across all your deployments in an environment. ### Status of pod before being created (only use when necessary) Use `kubectl describe pod ` to get the status of a pod before it is created. This will show you all the steps that Tensorkube takes to create a pod. It will also give you the time each of those steps take and whether there is any scope of optimisation or not.